Dynamic statistical network informatics

Kathleen Carley, Carnegie Mellon University

The basic research proposal aims to develop new dynamic statistical network techniques that will support the identification of structural features in communities or nation-states that can be leveraged to increase the resiliency, alter the distribution of power, support deterrence activities or stabilize or destabilize communities. At its core, developing this socio-cultural understanding (the socio-cognitive cultural map (SCM)) means collecting, reasoning about, visualizing and forecasting change in networks. However, these networks are not the traditional social networks but rather high-dimensional dynamic inferred networks relating actors at different levels of granularity (individuals and groups) to other actors and their activities, beliefs, and topics of concern, posing severe problems for the analyst.

The methods will be designed and assessed through the construction and assessment of SCMs for diverse contexts (resiliency, deterrence and cyber) and regions of interest (Syria/Iraq, Pacific Rim, and Global) using diverse data sources (questionnaire, news, subject matter expert assessments, and sensor data). The algorithm, procedures and associated tools developed in this project for identifying and visualizing SCMs, assessing resiliency and the impact of structural changes on resiliency will provide the DoD with a core operational capability to enhance predictive modeling, and support mission planning.